By Yaniv Vardi
Twenty billion dollars.
That is a lot of money. $20 billion is roughly the Gross Domestic Product of Nepal. It's also rumored to be the annual budget of the NSA. $20 billion also happens to be the value of energy used each year by the retail industry in the U.S. According to Adam Siegel of the Retail Industry Leaders Association, this creates a savings potential in the industry of roughly $3 billion (more than the GDP of Aruba).
At the macro level, a $3 billion industry-wide opportunity for savings (not to mention the potential environmental improvements) is a big deal. Even at the micro level, when we examine individual retail chains, we discover that excess energy consumption in retail can exceed 30 percent of total profits. With solutions that promote energy and operational efficiencies, we can do away with the waste and inject the savings directly to the bottom line.
Forward-thinking retail chains are accepting energy as a strategic asset. And, as such, they are finding ways to manage their energy consumption intelligently to minimize off-hour consumption and wrong building automation system (BAS) scheduling, antiquated technology solutions, poor maintenance and inefficient equipment, and eliminate undetected and resource-intensive failures.
Retailers must also have access to an advanced analytics system that can aggregate all of the granular device-level energy data. Based on this information, analytics can reveal usage patterns and trends, benchmark sites and identify maintenance issues before failures occur.
Powered by data and insights, retailers can then create processes that leverage this intelligence to reduce consumption across the retail chain (and increase corporate profits).
By using wireless sensor technology, we can observe the power consumption per device, per location, per unit of time. With this level of granularity, we can, for example, detect lighting systems or LCD screens which operate after hours, when the store is closed. Retailers that operate a building automation system can be alerted to overrides or poor scheduling of the system.
We can improve operational efficiency of our companies by shifting to predictive maintenance of our systems. That is, instead of investing resources in randomly scheduled maintenance, we can monitor energy usage at the device level and base our maintenance on data that points to an anomaly such as overconsumption, idling or under-consumption. When we optimize our maintenance schedules based on this information, we increase equipment life, decrease maintenance costs and eliminate equipment failures.
Our device-level data can also alert us to equipment that is functioning inefficiently. By benchmarking and comparing similar systems and locations, we can easily identify those which are underperforming, as well as track the effects of any maintenance or retrofitting projects.
But the payoffs go even further than the $3 billion. With solutions that are based on visibility, analytics and processes, retailers are now tracking their energy consumption at the device level, analyzing it and using the insights to understand ecosystem-level solutions -- eliminating waste and benefiting financially, environmentally and socially.
Image credit: Flickr/Random Retail
Yaniv Vardi, Chief Executive Officer at Panoramic Power. Yaniv is a seasoned executive with close to two decades of executive leadership experience in the Enterprise Solution Industry. As CEO of Panoramic Power, he oversees the day-to-day operations of the company as well as provides vision, strategic direction and focused execution for the company.